The ability to continually learning new knowledge is getting more and more important for machine learning models nowadays as the increasing demands of automation and the dynamic nature of our environment, e.g. the visual recognition system of the goods in the intelligent self-checkout system for smart retail should be able to classify the newly-added items or the existing items with new packing. In particular, the model cannot be trained from scratch whenever the classes or recognition targets increase. Instead, it needs to keep adapting
itself to learn new knowledge on the fly over time. Online continual learning (OCL) [1]} is one of the
topics getting popular these years to serve such purpose, where the machine learning agent continually learns a few new concepts every once in awhile without forgetting the others (i.e. what the agent has learnt previously).
